A point of interest (POI) refers to a location area in which a user frequently stays for a long time, for example an area that is of great importance to the user, such as a home, an office, or a frequently-visited supermarket.
Track information of daily activities of the user may be acquired by using a locating function, such as a Wi-Fi network, a Global Positioning System (GPS), and a base station identity (ID) of a terminal such as a mobile phone. The track information includes a large quantity of locating coordinate points with a locating deviation. The study on how to extract a POI of the user from the track information is of great value to context awareness and a location based service (LBS), and is also a research focus in the academia.
Currently, there is a method for exploring a POI based on multiple GPS track information of a user, and a main idea of the method is: first modeling multiple historical location data of the user by using a tree-like hierarchical pattern, and then proposing, based on the tree-like hierarchical pattern, an inference model that performs searching based on a hypertext subject, and establishing a link from a user to a location for a single visit of an individual.
However, in the foregoing method, a stay point of the user is extracted by using spatial and temporal dimensions. The stay point can represent only a single visit of the user, but cannot represent a POI place that is of great importance to the user. In addition, when a POI is being explored, only historical location data of the user is referred to, and therefore reliability and reference value of the explored POI is low.